A memetic algorithm for the optimal winner determination problem

Authors:
Dalila Boughaci;Belaïd Benhamou;Habiba Drias
Affiliations:
INCA/LSIS, CMI 39 rue Fredric Joliot-Curie, 13013, Marseille, France and LRIA/USTHB, BP 32 El-Alia, Beb-Ezzoaur, 16111, Algiers, Algeria;INCA/LSIS, CMI 39 rue Fredric Joliot-Curie, 13013, Marseille, France;LRIA/USTHB, BP 32 El-Alia, Beb-Ezzoaur, 16111, Algiers, Algeria
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
Year:
2009

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Abstract

In this paper, we propose a memetic algorithm for the optimal winner determination problem in combinatorial auctions. First, we investigate a new selection strategy based on both fitness and diversity to choose individuals to participate in the reproduction phase of the memetic algorithm. The resulting algorithm is enhanced by using a stochastic local search (SLS) component combined with a specific crossover operator. This operator is used to identify promising search regions while the stochastic local search performs an intensified search of solutions around these regions. Experiments on various realistic instances of the considered problem are performed to show and compare the effectiveness of our approach.